Brain-inspired energy efficient technologies for next-generation artificial intelligence

Hillel J. Chiel, Jay S. Coggan, Gourav Datta, Jean-Marc Fellous, William R. P. Nourse, Roger D. Quinn, Peter J. Thomas

Open source

DOI: 10.1007/s00422-026-01038-4
Published: 2026-02-23
Container: Biological Cybernetics
Publisher: Springer Science and Business Media LLC
Open access: unknown

Credibility signals

uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

supportingDOI registered: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
supportingDOI resolves: A matching record was returned by Crossref. Source: Crossref; license: CC0 metadata
not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility. Source: DOAJ; license: CC0
not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredROR affiliation: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete. Source: Retraction Watch; license: CC BY 4.0
not scoredOpen access status: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication license: Not checked or no result supplied; no credibility inference made. Source: No authority result supplied; license: Unknown
not scoredPublication version: A publication version was supplied but is not scored. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer
supportingMetadata completeness: All 6 scored descriptive metadata groups are present. Source: Normalized work metadata; license: Caller-provided; provenance license not supplied to scorer

Cite this work

BibTeX

@article{allodium:10.1007/s00422-026-01038-4,
  title = {Brain-inspired energy efficient technologies for next-generation artificial intelligence},
  author = {Hillel J. Chiel and Jay S. Coggan and Gourav Datta and Jean-Marc Fellous and William R. P. Nourse and Roger D. Quinn and Peter J. Thomas},
  year = {2026},
  journal = {Biological Cybernetics},
  doi = {10.1007/s00422-026-01038-4},
  url = {https://doi.org/10.1007/s00422-026-01038-4}
}

RIS

TY  - JOUR
TI  - Brain-inspired energy efficient technologies for next-generation artificial intelligence
AU  - Hillel J. Chiel
AU  - Jay S. Coggan
AU  - Gourav Datta
AU  - Jean-Marc Fellous
AU  - William R. P. Nourse
AU  - Roger D. Quinn
AU  - Peter J. Thomas
PY  - 2026
JO  - Biological Cybernetics
DO  - 10.1007/s00422-026-01038-4
UR  - https://doi.org/10.1007/s00422-026-01038-4
ER  -

APA

Chiel, H. J., Coggan, J. S., Datta, G., Fellous, J., Nourse, W. R. P., Quinn, R. D., & Thomas, P. J. (2026). Brain-inspired energy efficient technologies for next-generation artificial intelligence. Biological Cybernetics. https://doi.org/10.1007/s00422-026-01038-4

Source records

crossref · retrieved 2026-09-26T15:53:00.997Z